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MSc Data Science lecture notes, University of Pisa

Typeset lecture notes for the MSc in Data Science & Business Informatics, University of Pisa. This is the root of the collection: each course is a self-contained LaTeX project, published as its own repository, and shares one house style. The courses span three academic years, from 2024/25 to 2026/27, and are at different stages of completion (see the table below).

⚠️ Disclaimer. These notes are open educational content created by a student. They are not an academic source and may contain inaccuracies. You may freely share, modify, and reuse this material for educational and non-commercial purposes with appropriate attribution. The content is a personal interpretation of the professors' course materials and should not replace official teaching resources. I assume no responsibility for any errors or misinterpretations.

The notes were produced with an AI-in-the-middle workflow: a first human pass, then Claude Code to support formulation, understanding, and rewriting, followed by a final human review.

If you find errors, have suggestions, or spot unintentionally included copyrighted material (which I will promptly remove on notification), contact me at sclfnc@proton.me.

Courses

Ten courses, each a standalone LaTeX project with its own README.md, compilable and clonable on its own. Status: ✅ done · 🚧 in progress · 📝 to do.

Folder Course Academic year Status
dm-notes Data Mining 2024/25
o4ds-notes Optimization for Data Science 2024/25
sds-notes Statistics for Data Science 2024/25
sna-notes Social Network Analysis 2024/25
lds-notes Laboratory of Data Science 2025/26
lids-notes Legal Issues in Data Science 2025/26
bpm-notes Business Process Modeling 2025/26 🚧
mddmm-notes Model-Driven Decision-Making Methods 2025/26
aif-notes Artificial Intelligence Fundamentals 2026/27 📝
alcna-notes Advanced Laboratory of Complex Network Analysis 2026/27 📝

Shared house style

Every course uses one house style. Three files are byte-identical across the whole collection, and this root holds their canonical copy:

  • main.tex: the entry point of a course. It only loads the shared preamble and the course file; it carries no content of its own.
  • src/housestyle.tex: geometry, colors, section and ToC formatting, running heads, and the math environments (theorem, definition, and the like).
  • src/common-preamble.tex: the shared package set.

Each course additionally carries its own src/course.tex (title metadata, math macros, boxes, hyperref/cleveref, bibliography, and the \input{sec/...} list), plus sec/ (the body), and, where the notes have diagrams, img/.

The copies in the root are the source of truth. When a shared file changes, it is edited here and propagated to the courses by hand; the copies are kept identical (verified by comparing checksums), not linked. The root main.tex is a template, not a document: it does not compile on its own, because it expects a per-course src/course.tex that lives in each course, not here.

Working notes and authoring skills

Two more things live in this root and describe how the notes are written, not the notes themselves. They apply across the whole collection and are tracked only here (each course ignores them):

  • CLAUDE.md: the working agreement followed while authoring, in English. It fixes the register (a formal teaching voice for a CS reader), the priorities (precision, then clarity, then detail, then coherence), the build and revision workflow, and the layout and commit conventions the courses share. It is written for an AI-assisted workflow but reads as a plain style-and-process guide.
  • .claude/skills/: five authoring standards, each a self-contained SKILL.md. notes-writing is the prose and revision standard (cadence, banned words, the no-em-dash rule, the %-comment revision method); tex-standard is the LaTeX and typography standard (math delimiters, theorem environments, tables, figures, cross-references); notation-check verifies symbols and terms against a course's notation lock; figure-verify checks a figure's claims (a net's firings, node and edge counts, an optimum) before it is trusted or drawn; new-course scaffolds a conformant course folder. Each states the rule independently of any single course.

Build a course

Build any course from its own folder root:

cd o4ds-notes
latexmk main.tex

latexmk runs pdflatex (and Biber, where a course uses it) as many times as needed, writes auxiliaries to build/, and leaves main.pdf in the folder root. Each course's README.md gives the by-hand fallback and notes any per-course quirk. A standard TeX Live installation is enough; alternatively, upload a course folder to Overleaf and set its main.tex as the main document.

Credits

Written by Francesco Secoli, revised with the help of Claude Code: the course slides and lectures were transcribed and refined into LaTeX, then reworked into standalone notes. Based on the MSc in Data Science & Business Informatics, University of Pisa (a.y. 2024/25 and 2025/26, per course). Contributions welcome: open an issue or a pull request on the relevant course repository.

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Lecture notes for the MSc in Data Science & Business Informatics, University of Pisa (10 courses as submodules)

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